Machine learning is a field of artificial intelligence that allows computer-implemented systems to perform a task without the use of task-specific code. Machine learning systems may be trained to progressively improve performance of a task using sets of training data. In supervised machine learning, annotated data (e.g., data with a labeled input and desired output) can be used to “train” a machine learning model. During training, parameters (e.g., weights and/or biases) of the machine learning model are adjusted so that the output of the machine learning model for a given input matches the desired output from the annotated data. Accuracy and/or predictive value of machine learning models are often a function of the quantity and quality of data used to train the machine learning model.